CN106251045A - Distribution network reliability appraisal procedure based on multiple leading factor - Google Patents

Abstract

A kind of distribution network reliability appraisal procedure based on multiple leading factor: set up according to the topological relation of power distribution network and include that five kinds affect the distribution network failure of the fault category of controller switching equipment duty in power distribution network and affect classification chart, determine the weight of five class faults in each controller switching equipment respectively；Calculate the power distribution network shared device fault rate of controller switching equipment, the natural disaster fault rate of controller switching equipment respectively；Determine eight class power distribution network shared device defect weight in each controller switching equipment；Calculate the distribution shared device defect state fault rate of controller switching equipment；Calculate the correction natural disaster fault rate of controller switching equipment；Calculating equipment correction fault rate；Calculate the reliability index of power distribution network.The present invention, by research major network and the environmental factors impact on Distribution Network Equipment running status, sets up fault rate correction model based on component equipment running status and method；And analyze process according to distribution network failure mode influences, set up evaluating reliability of distribution network model, provide reference for scientifically carrying out evaluating reliability of distribution network.

Description

Distribution network reliability appraisal procedure based on multiple leading factor

Technical field

The present invention relates to a kind of power system appraisal procedure.Particularly relating to one can be the truest in conjunction with practical situation Ground carries out the distribution network reliability appraisal procedure based on multiple leading factor of reliability assessment to power distribution network.

Background technology

Power system by generating electricity, transmit electricity, each several part system such as distribution and electricity consumption forms.Distribution system arrives as power transmission Last ring of user, the tightst with contacting of user, the impact on user is the most direct, is to ensure that power supply quality, carries The key link of high operation of power networks efficiency, Innovative User service.It is the critical stage of electric energy supply and distribution.Distribution system Run directly concern user can normal reliable electricity consumption, when these equipment are due to fault, maintenance repair, construction or other reasons When causing stopping transport, whole power system will stop the power supply to user, until the fault of distribution system and equipment thereof is excluded Or repair, normal power supply could be continued, so distribution Power System Reliability index set reflects whole NETWORK STRUCTURE PRESERVING POWER SYSTEM and fortune Row characteristic.In recent years, along with power supply quality requirement is improved constantly by user, distribution Power System Reliability obtains people and gets more and more Attention.

It is applied to distribution system reliability evaluation common method and mainly has simulation method and the big class of analytic method two.According to power distribution system Pattern, complexity and the difference of required analysis depth of system, the appraisal procedure of employing is the most different.Simulation method In typical method be Monte Carlo Analogue Method, Monte Carlo Analogue Method be utilize computer produce the random number inefficacy to element Event is sampled constituting thrashing event set, then calculates a class method of reliability index by the way of statistics.The party Method is applicable to solve the reliability of complication system, but there is bigger contradiction between computational accuracy and calculating time.Analytic method mould Type is accurate, it is simple to analyzes the Various Components impact on distribution network reliability, is more widely applied in evaluating reliability of distribution network. For radial pattern distribution system, directly use train reliability assessment principle, by element one by one is carried out accident analysis, The method observing and listing the failure effect table of each load point, can calculated load point and the evenness of system very easily Can index.And for complicated distribution, such as parallel-connection structure and network structure, owing to the state of system is more, the most first use The method choice thrashing states such as state space method and some other method for simplifying, such as network reduction method, then according to each The consequence of failure state and the reliability index of the probability calculation whole system of appearance thereof.

Equipment failure rate parameter employed in conventional electrical distribution net reliability assessment is to unite according to relevant device historical failure Result obtained by meter, when carrying out distribution network reliability and calculating, the single meansigma methods of many employings is as component reliability parameter, Can not effectively reflect the variation tendency of distribution network equipment state level, it is impossible to accurately embody the achieved reliability water that power distribution network is current Flat.Therefore, the not enough structure distribution network reliability based on multiple dominant factor for conventional electrical distribution net reliability estimation method refers to Mark and weakness zone appraisal procedure, Distribution Network Equipment fault rate and the power distribution network physical device shape that will obtain with historical statistics result State combines, and obtains considering the failure rate model of the virtual conditions such as period, environment and external force factor residing for Distribution Network Equipment, in conjunction with Distribution feeder zone method proposes distribution network reliability evaluation method based on equipment failure rate running status correction, has good Using value.

Distribution network reliability is the comprehensive embodiment of distribution net work structure, technical equipment and management level.Equipment failure rate As the important parameter in Calculation of Reliability, whether the science of its correction model determines the result of evaluating reliability of distribution network is No have actual directive significance, therefore, uses the equipment failure rate accurately reflecting equipment operation condition to be by science power distribution network The prerequisite of reliability assessment.The reliability data drawn in statistics by longtime running record, sometimes due to reliably Property management pay little attention to or other factors, can not accurately and comprehensively reflect equipment running status；Further, since power equipment The variation of running environment, equipment operating condition is also not quite similar, and directly quotes the national Huo Ge great district range statistics published Average data, necessarily lead to bigger error so that reliability assessment result loses meaning.

On the basis of the Distribution Network Equipment fault rate that historical statistics result obtains, by Distribution Network Equipment failure cause is entered Capable analysis, inside residing for Distribution Network Equipment, self-operating state and extraneous two major influence factors of natural environment are to equipment Fault rate carries out quantifying to revise, and builds Distribution Network Equipment fault rate running status correction model, can realize history and add up on a large scale Result and the combination of power distribution network physical device state, solve the deficiency of conventional electrical distribution net reliability estimation method.

Use analytic method to carry out reliability assessment, by Failure Mode Effective Analysis, set up each equipment forecast accident The system failure affects classification chart, in conjunction with the distribution feeder zone method of Failure Mode Effective Analysis process can be simplified, propose based on The distribution network reliability evaluation method of equipment failure rate running status correction, accurate embodies distribution network reliability level full and accurately.

Summary of the invention

The technical problem to be solved is to provide one can be in order to more rationally to calculate reflection distribution practically The load point of net achieved reliability level and the distribution network reliability based on multiple leading factor of Reliability Index Appraisal procedure.

The technical solution adopted in the present invention is: a kind of distribution network reliability assessment side based on multiple leading factor Method, comprises the steps:

1) set up distribution network failure according to the topological relation of power distribution network and affect classification chart, wherein, described distribution network failure Affect classification chart and include that five kinds affect the fault category of controller switching equipment duty in power distribution network and include: distribution shared device is former Cause, external force destruction, natural climatic factor, user malfunction impact and major network fault；

2) according to function and the external environment condition of each controller switching equipment, five class faults in each controller switching equipment i are determined respectively Weight w_{(i) event j}, wherein j is failure mode, j=1,2,3,4,5；

3) by basic fault rate λ of i-th controller switching equipment_(i)Substitution-type fault rate formula λ=λ_(i)×w_{(i) event j}, respectively Calculate power distribution network shared device fault rate λ of i-th controller switching equipment_{Join (i)}, and the natural disaster fault rate of i-th controller switching equipment λ_{From (i)}；

4) according to function and the external environment condition of each controller switching equipment, determine that in each controller switching equipment i, eight class power distribution networks are public Equipment deficiency weight w_{I () joins k}, wherein, k=1,2,3,4,5,6,7,8；Eight described class defects specifically include: planning and designing are not Week, construction and installation reason, product quality reasons, ageing equipment, checking experiment quality is bad, operational management is improper, power failure responsibility Reason the cleerest and the most peaceful low pressure facility failure；

5) will i-th controller switching equipment refer to relative to the equipment state degree correction of kth class power distribution network shared device defect Number c_(i)k, relative to kth class power distribution network shared device defect weight w in i-th controller switching equipment_{I () joins k}, i-th controller switching equipment first Class fault right weight w_{(i) event 1}, and basic fault rate λ of i-th controller switching equipment in power distribution network_(i)Substitute into equipment deficiency status fault Rate correction formula:

Calculate distribution shared device defect state fault rate λ of i-th controller switching equipment_{Join and repair (i)}；

6) by fault rate monthly total precipitation modified index M of the m month_(m), moon thunderbolt modified index T_(m), i-th controller switching equipment Lightning fault weight w_{(i) gas 1}, strong wind and heavy rain fault right weight w_{(i) gas 2}, other meteorological fault right weight w_{(i) gas 3}, substitute into the event of following equipment Barrier rate natural disaster correction formula, calculates correction natural disaster fault rate λ of i-th controller switching equipment_{Review one's lessons by oneself (i)},

λ_{Review one's lessons by oneself (i)}=T_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 1}+M_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 2}+λ_(i)×w_{(i) event 3}×w_{(i) gas 3} (2)

Wherein, T_(m)It it is the fault rate moon thunderbolt modified index of the m month；λ_(i)For the base of i-th controller switching equipment in power distribution network Plinth fault rate；w_{(i) event 3}For i-th controller switching equipment the 3rd class fault right weight in power distribution network；w_{(i) gas 1}Set for i-th distribution in power distribution network Standby lightning fault weight；M_(m)The fault rate monthly total precipitation modified index of the m month；w_{(i) gas 2}Set for i-th distribution in power distribution network Standby strong wind and heavy rain fault right weight w_{(i) gas 2}、w_{(i) gas 3}For other meteorological fault right weight w of i-th controller switching equipment in power distribution network_{(i) gas}；

7) by revised power distribution network shared device defect state fault rate λ_{Join and repair (i)}, natural disaster fault rate λ_{Review one's lessons by oneself (i)}, i-th Individual controller switching equipment first kind fault right weight w_{(i) event 1}, i-th controller switching equipment the 3rd class fault right weight w_{(i) event 3}With i-th controller switching equipment Basic fault rate λ_(i)Substitute into following equipment correction fault formula and calculate equipment correction fault rate λ_{Repair (i)}:

λ_{Repair (i)}=λ_{Join and repair (i)}+λ_{Review one's lessons by oneself (i)}+λ_(i)(1-w_{(i) event 1}-w_{(i) event 3}) (3)；

8) according to step 7) in equipment correction fault rate λ that obtains_{Repair (i)}Calculate the reliability index of power distribution network.

Step 3) described in basic fault rate λ of i-th controller switching equipment_(i)Refer to i-th controller switching equipment institute in a year The number of times broken down；Power distribution network shared device fault rate λ of i-th controller switching equipment is obtained according to type fault rate formula_{Join (i)} =λ_(i)×w_{(i) event 1}, natural disaster fault rate λ of i-th controller switching equipment_{From (i)}=λ_(i)×w_{(i) event 3}。

Step 6) described in fault rate monthly total precipitation modified index M of the m month_(m)Computing formula be:

$M_{\left(m\right)}=\frac{12{\stackrel{\‾}{H}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{H}}_{\left(i\right)}}---\left(4\right)$

Wherein, m represents month,Representing the monthly precipitation of the m-th moon, computing formula is:

${\stackrel{\‾}{H}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{H}_{\left(m\right)l}}{n}---\left(5\right)$

Wherein, l is the data statistics time, for p to p+n year, H_(m)lRepresent the monthly total precipitation of the l m-th moon.

Step 6) described in the m month the fault rate moon thunderbolt modified index T_(m)Computing formula be:

$T_{\left(m\right)}=\frac{12{\stackrel{\‾}{Y}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{Y}}_{\left(i\right)}}---\left(6\right)$

Wherein m represents month,Representing the monthly number of lightning strokes of the m-th moon, computing formula is:

${\stackrel{\‾}{Y}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{Y}_{\left(m\right)l}}{n}---\left(7\right)$

Wherein, l is the data statistics time, for p to p+n year, Y_(m)jRepresent the number of lightning strokes of the l m-th moon.

Step 8) described in distribution network reliability index, including system System average interruption frequency, system averagely have a power failure continue Time, average power supply availability and the total electricity of system are not enough.

The distribution network reliability appraisal procedure based on multiple leading factor of the present invention, in order to more rationally practically Calculate the Reliability Index of reflection power distribution network achieved reliability level.By studying major network and environmental factors to power distribution network The impact of equipment running status, sets up fault rate correction model based on component equipment running status and method；And according to distribution Net Failure Mode Effective Analysis process, sets up evaluating reliability of distribution network model, for scientifically carrying out evaluating reliability of distribution network Reference is provided.

Accompanying drawing explanation

Fig. 1 is Distribution Network Equipment failure reason analysis schematic diagram；

Fig. 2 is the distribution network reliability appraisal procedure based on multiple leading factor of the present invention；

Fig. 3 is present example distribution network systems feeder line the first schematic diagram；

Fig. 4 is present example distribution network systems feeder line the second schematic diagram.

Detailed description of the invention

Below in conjunction with embodiment and accompanying drawing, the distribution network reliability based on multiple leading factor of the present invention is assessed Method is described in detail.

The distribution network reliability appraisal procedure based on multiple leading factor of the present invention, by research major network, external force And the impact that environmental factors is on Distribution Network Equipment running status, set up fault rate correction mould based on component equipment running status Type and method；And in conjunction with the concept of Feeder partitioning, analyze process according to distribution network failure mode influences, set up power distribution network reliable Property assessment models, for scientifically carry out evaluating reliability of distribution network provide reference.

Power distribution network is mainly made up of equipment such as aerial line, cable, distribution transforming, chopper, switch elements.Device fails or Person is produced, by pre-arranged, the main cause that stoppage in transit is thrashing, and equipment failure rate is the crucial ginseng of evaluating reliability of distribution network Number, therefore reliability assessment first has to determine the equipment outage model of science.The present invention is directed to physical device fault rate by distribution Many-sided cause influence such as net shared device and natural climate and there is probabilistic feature, set up equipment failure rate and run State revision model.

As in figure 2 it is shown, the distribution network reliability appraisal procedure based on multiple leading factor of the present invention, including as follows Step:

1) set up distribution network failure according to the topological relation of power distribution network and affect classification chart, concrete classification situation such as Fig. 1 institute Showing, wherein, described distribution network failure affects classification chart and includes that five kinds affect the fault of controller switching equipment duty in power distribution network Classification includes: distribution shared device reason, external force destruction, natural climatic factor, user malfunction impact and major network fault；

2) according to function and the external environment condition of each controller switching equipment, five class faults in each controller switching equipment i are determined respectively Weight w_{(i) event j}, wherein j is failure mode, j=1,2,3,4,5；Factor of equipment failure and its weight title corresponding relation such as table 1 Shown in.

Table 1 factor of equipment failure and its weight title corresponding relation

Structure factor of equipment failure weight matrix is as follows:

Wherein, w_{(i) event j}Represent for the i-th kind equipment, the weighted value of jth kind failure factor；

3) by basic fault rate λ of i-th controller switching equipment_(i)Substitution-type fault rate formula λ=λ_(i)×w_{(i) event j}, respectively Calculate power distribution network shared device fault rate λ of i-th controller switching equipment_{Join (i)}, and the natural disaster fault rate of i-th controller switching equipment λ_{From (i)}；

Basic fault rate λ of described i-th controller switching equipment_(i)Refer to that i-th controller switching equipment was broken down in 1 year Number of times；Power distribution network shared device fault rate λ of i-th controller switching equipment is obtained according to type fault rate formula_{Join (i)}=λ_(i)× w_{(i) event 1}, natural disaster fault rate λ of i-th controller switching equipment_{From (i)}=λ_(i)×w_{(i) event 3}。

4) according to function and the external environment condition of each controller switching equipment, determine that in each controller switching equipment i, eight class power distribution networks are public Equipment deficiency weight w_{I () joins k}, wherein, k=1,2,3,4,5,6,7,8；Eight described class defects specifically include: planning and designing are not Week, construction and installation reason, product quality reasons, ageing equipment, checking experiment quality is bad, operational management is improper, power failure responsibility Reason the cleerest and the most peaceful low pressure facility failure；Wherein, distribution shared device failure factor and its weight title corresponding relation such as table 2 institute Show.

Table 2 distribution shared device failure factor and its weight title corresponding relation

Structure factor of equipment failure weight matrix is as follows:

Wherein, w_{I () joins k}(1≤k≤8) represent for the i-th kind equipment, the weighted value of kth kind factor of equipment failure.

5) will i-th controller switching equipment refer to relative to the equipment state degree correction of kth class power distribution network shared device defect Number c_(i)k, relative to kth class power distribution network shared device defect weight w in i-th controller switching equipment_{I () joins k}, i-th controller switching equipment first Class fault right weight w_{(i) event 1}, and basic fault rate λ of i-th controller switching equipment in power distribution network_(i)Substitute into equipment deficiency status fault Rate correction formula:

Calculate distribution shared device defect state fault rate λ of i-th controller switching equipment_{Join and repair (i)}；

Wherein, equipment electric insulation state revision index is as shown in table 3 with its designation corresponding relation.

Table 3 distribution shared device state degree and its designation corresponding relation

Structure equipment state degree matrix is as follows:

$C=\left[\begin{array}{cccc}{c}_{\left(1\right)1}& c_{\left(1\right)2}& \mathrm{...}& c_{\left(1\right)8}\\ c_{\left(2\right)1}& c_{\left(2\right)2}& \mathrm{...}& c_{\left(2\right)8}\\ \mathrm{...}& \mathrm{...}& \mathrm{...}& \mathrm{...}\\ c_{\left(5\right)1}& c_{\left(5\right)2}& \mathrm{...}& c_{\left(5\right)8}\end{array}\right]---\left(4\right)$

6) by fault rate monthly total precipitation modified index M of the m month_(m), moon thunderbolt modified index T_(m), i-th controller switching equipment Lightning fault weight w_{(i) gas 1}, strong wind and heavy rain fault right weight w_{(i) gas 2}, other meteorological fault right weight w_{(i) gas 3}, substitute into the event of following equipment Barrier rate natural disaster correction formula, calculates correction natural disaster fault rate λ of i-th controller switching equipment_{Review one's lessons by oneself (i)},

λ_{Review one's lessons by oneself (i)}=T_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 1}+M_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 2}+λ_(i)×w_{(i) event 3}×w_{(i) gas 3} (5)

Wherein, T_(m)It it is the fault rate moon thunderbolt modified index of the m month；λ_(i)For the base of i-th controller switching equipment in power distribution network Plinth fault rate；w_{(i) event 3}For i-th controller switching equipment the 3rd class fault right weight in power distribution network；w_{(i) gas 1}Set for i-th distribution in power distribution network Standby lightning fault weight；M_(m)The fault rate monthly total precipitation modified index of the m month；w_{(i) gas 2}Set for i-th distribution in power distribution network Standby strong wind and heavy rain fault right weight w_{(i) gas 2}、w_{(i) gas 3}For other meteorological fault right weight w of i-th controller switching equipment in power distribution network_{(i) gas}；

Fault rate monthly total precipitation modified index M of the described m month_(m)Computing formula be:

$M_{\left(m\right)}=\frac{12{\stackrel{\‾}{H}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{H}}_{\left(i\right)}}---\left(6\right)$

Wherein, m represents month,Representing the monthly precipitation of the m-th moon, computing formula is:

${\stackrel{\‾}{H}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{H}_{\left(m\right)l}}{n}---\left(7\right)$

Wherein, l is the data statistics time, for p to p+n year, H_(m)lRepresent the monthly total precipitation of the l m-th moon.

Fault rate moon thunderbolt modified index T of the described m month_(m)Computing formula be:

$T_{\left(m\right)}=\frac{12{\stackrel{\‾}{Y}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{Y}}_{\left(i\right)}}---\left(8\right)$

Wherein m represents month,Representing the monthly number of lightning strokes of the m-th moon, computing formula is:

${\stackrel{\‾}{Y}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{Y}_{\left(m\right)l}}{n}---\left(9\right)$

Wherein, l is the data statistics time, for p to p+n year, Y_(m)jRepresent the number of lightning strokes of the l m-th moon.

7) by revised power distribution network shared device defect state fault rate λ_{Join and repair (i)}, natural disaster fault rate λ_{Review one's lessons by oneself (i)}, i-th Individual controller switching equipment first kind fault right weight w_{(i) event 1}, i-th controller switching equipment the 3rd class fault right weight w_{(i) event 3}With i-th controller switching equipment Basic fault rate λ_(i)Substitute into following equipment correction fault formula and calculate equipment correction fault rate λ_{Repair (i)}:

λ_{Repair (i)}=λ_{Join and repair (i)}+λ_{Review one's lessons by oneself (i)}+λ_(i)(1-w_{(i) event 1}-w_{(i) event 3}) (10)；

8) according to step 7) in equipment correction fault rate λ that obtains_{Repair (i)}Calculate the reliability index of power distribution network.

Described distribution network reliability index, including system System average interruption frequency SAIFI, system System average interruption duration SAIDI, average power supply availability ASAI and the total electricity of system are less than ENS.

Instantiation be given below:

MATLAB is the business mathematics software that MathWorks company of the U.S. produces, and is one and can be used for algorithm development, data Visualization, data analysis and the advanced techniques computational language of numerical computations and interactive environment.The present invention is with MATLAB as base Plinth, it is achieved that distribution power automation terminal Optimal Allocation Model, is applied wherein by the present invention.

1) invention backgrounds

For checking effectiveness of the invention, the one group of simply connected network diagram choosing certain city's power distribution network is analyzed object as an example, is ground Study carefully the thin of the grid structure of analysis example electrical network, equipment state assessment result, this region of analyzing influence and emphasis user dependability Weak link, checking effectiveness of the invention and practicality.Choose certain transformer station of city 10kV feeder line i.e. feeder line one and feeder line two conduct Aerial line simply connected network diagram example, it is adaptable to feeder line one and feeder line two schematic network structure of instance analysis, respectively such as Fig. 3 and figure Shown in 4.

Mainly for five kinds of power distribution network typical cases such as aerial line, cable, chopper, switch and distribution transformers in implementation process Equipment carries out distribution network reliability analysis based on physical device state.By statistics, feeder line one and feeder line two are comprised all kinds of Type number of devices is as shown in table 4.

Device type and scale contained by table 4 power distribution network

Implement place in July, 2010 in June, 2014 Distribution Network Equipment failure factor record by analyzing, obtain five kinds and set Standby fault parameter is as shown in table 5.

Table 5 equipment fault parameter

It addition, the mean failure rate location isolation time of switch is 1h；The upstream, trouble point of switch restores electricity the operating time For 0.78h.

2) factor of equipment failure weight matrix

Implement place in July, 2010 in June, 2014 Distribution Network Equipment failure factor record by analyzing, obtain implementing ground Point distribution net equipment failure factor weight matrix, distribution shared device failure factor matrix, natural disaster meteorological effect factor weight Matrix is as shown in table 6 to table 8.

The factor of equipment failure weight matrix of distribution is as shown in table 6.

Table 6 factor of equipment failure weight matrix

Distribution net equipment electric insulation defect factors weight matrix is as shown in table 7.

Table 7 distribution shared device failure factor weight matrix

Implement place natural disaster meteorological effect factor weight matrix as shown in table 8.

Table 8 natural disaster meteorological effect factor weight matrix

Equipment	Thunderbolt	Strong wind and heavy rain	Other
				Cable	0.357	0.143	0.500
Aerial line	0.593	0.261	0.147
				Chopper	0.000	0.000	0.000
Switch	0.735	0.143	0.122
				Distribution transforming	0.385	0.462	0.154

3) equipment fault influence factor modified index

Table 9 distribution shared device failure factor correction factor matrix

The monthly precipitation of table 10 and thunderbolt correction factor

Revise the moon	Precipitation correction factor	Thunderbolt correction factor
			June	2.22	3.39
October	0.44	0.18

4) reliability interpretation of result

The Reliability Index contrast situation in different months is as shown in table 11.

Reliability Index contrast under the conditions of table 11 Different climate

Reliability Index	June index size	October index size
			SAIFI [secondary/(user a)]	4.3489	2.9713
SAIDI [h/ (user a)]	14.4745	9.9861
			ASAI [%]	99.83	99.89
ENS[kW·h/a]	18.3357	12.6528

By being analyzed the Reliability Index of table 11, the difference of difference month Reliability Index is relatively Greatly, its basic reason is that weather conditions are different, cause the fault rate of Distribution Network Equipment element to change, thus have impact on and be System reliability index.

Claims (5)

1. a distribution network reliability appraisal procedure based on multiple leading factor, it is characterised in that comprise the steps:

1) set up distribution network failure according to the topological relation of power distribution network and affect classification chart, wherein, described distribution network failure impact Classification chart includes that five kinds affect the fault category of controller switching equipment duty in power distribution network and include: distribution shared device reason, outer Power destruction, natural climatic factor, user malfunction impact and major network fault；

2) according to function and the external environment condition of each controller switching equipment, the weight of five class faults in each controller switching equipment i is determined respectively w_{(i) event j}, wherein j is failure mode, j=1,2,3,4,5；

3) by basic fault rate λ of i-th controller switching equipment_(i)Substitution-type fault rate formula λ=λ_(i)×w_{(i) event j}, calculate respectively Power distribution network shared device fault rate λ of i controller switching equipment_{Join (i)}, and natural disaster fault rate λ of i-th controller switching equipment_{From (i)}；

4) according to function and the external environment condition of each controller switching equipment, eight class power distribution network shared device in each controller switching equipment i is determined Defect weight w_{I () joins k}, wherein, k=1,2,3,4,5,6,7,8；Eight described class defects specifically include: planning and designing are inconsiderate, execute Work install reason, product quality reasons, ageing equipment, checking experiment quality is bad, operational management is improper, power failure liability cause not Cleer and peaceful low pressure facility failure；

5) by i-th controller switching equipment relative to the equipment state degree modified index of kth class power distribution network shared device defect c_(i)k, relative to kth class power distribution network shared device defect weight w in i-th controller switching equipment_{I () joins k}, the i-th controller switching equipment first kind Fault right weight w_{(i) event 1}, and basic fault rate λ of i-th controller switching equipment in power distribution network_(i)Substitute into equipment deficiency status fault rate Correction formula:

Calculate distribution shared device defect state fault rate λ of i-th controller switching equipment_{Join and repair (i)}；

6) by fault rate monthly total precipitation modified index M of the m month_(m), moon thunderbolt modified index T_(m), the thunder of i-th controller switching equipment Hit fault right weight w_{(i) gas 1}, strong wind and heavy rain fault right weight w_{(i) gas 2}, other meteorological fault right weight w_{(i) gas 3}, substitute into following equipment failure rate Natural disaster correction formula, calculates correction natural disaster fault rate λ of i-th controller switching equipment_{Review one's lessons by oneself (i)},

λ_{Review one's lessons by oneself (i)}=T_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 1}+M_(m)×λ_(i)×w_{(i) event 3}×w_{(i) gas 2}+λ_(i)×w_{(i) event 3}×w_{(i) gas 3} (2)

Wherein, T_(m)It it is the fault rate moon thunderbolt modified index of the m month；λ_(i)For the basis event of i-th controller switching equipment in power distribution network Barrier rate；w_{(i) event 3}For i-th controller switching equipment the 3rd class fault right weight in power distribution network；w_{(i) gas 1}For i-th controller switching equipment in power distribution network Lightning fault weight；M_(m)The fault rate monthly total precipitation modified index of the m month；w_{(i) gas 2}For i-th controller switching equipment in power distribution network Strong wind and heavy rain fault right weight w_{(i) gas 2}、w_{(i) gas 3}For other meteorological fault right weight w of i-th controller switching equipment in power distribution network_{(i) gas}；

7) by revised power distribution network shared device defect state fault rate λ_{Join and repair (i)}, natural disaster fault rate λ_{Review one's lessons by oneself (i)}, i-th joins Electricity equipment first kind fault right weight w_{(i) event 1}, i-th controller switching equipment the 3rd class fault right weight w_{(i) event 3}Base with i-th controller switching equipment Plinth fault rate λ_(i)Substitute into following equipment correction fault formula and calculate equipment correction fault rate λ_{Repair (i)}:

λ_{Repair (i)}=λ_{Join and repair (i)}+λ_{Review one's lessons by oneself (i)}+λ_(i)(1-w_{(i) event 1}-w_{(i) event 3}) (3)；

8) according to step 7) in equipment correction fault rate λ that obtains_{Repair (i)}Calculate the reliability index of power distribution network.

Distribution network reliability appraisal procedure based on multiple leading factor the most according to claim 1, its feature exists In, step 3) described in basic fault rate λ of i-th controller switching equipment_(i)Refer to that i-th controller switching equipment was occurred in 1 year The number of times of fault；Power distribution network shared device fault rate λ of i-th controller switching equipment is obtained according to type fault rate formula_{Join (i)}=λ_(i) ×w_{(i) event 1}, natural disaster fault rate λ of i-th controller switching equipment_{From (i)}=λ_(i)×w_{(i) event 3}。

Distribution network reliability appraisal procedure based on multiple leading factor the most according to claim 1, its feature exists In, step 6) described in fault rate monthly total precipitation modified index M of the m month_(m)Computing formula be:

$M_{\left(m\right)}=\frac{12{\stackrel{\‾}{H}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{H}}_{\left(i\right)}}---\left(4\right)$

Wherein, m represents month,Representing the monthly precipitation of the m-th moon, computing formula is:

${\stackrel{\‾}{H}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{H}_{\left(m\right)l}}{n}---\left(5\right)$

Wherein, l is the data statistics time, for p to p+n year, H_(m)lRepresent the monthly total precipitation of the l m-th moon.

Distribution network reliability appraisal procedure based on multiple leading factor the most according to claim 1, its feature exists In, step 6) described in fault rate moon thunderbolt modified index T of the m month_(m)Computing formula be:

$T_{\left(m\right)}=\frac{12{\stackrel{\‾}{Y}}_{\left(m\right)}}{\underset{i=1}{\overset{12}{\Σ}}{\stackrel{\‾}{Y}}_{\left(i\right)}}---\left(6\right)$

Wherein m represents month,Representing the monthly number of lightning strokes of the m-th moon, computing formula is:

${\stackrel{\‾}{Y}}_{\left(m\right)}=\frac{\underset{l=p}{\overset{p+n}{\Σ}}{Y}_{\left(m\right)l}}{n}---\left(7\right)$

Wherein, l is the data statistics time, for p to p+n year, Y_(m)jRepresent the number of lightning strokes of the l m-th moon.

Distribution network reliability appraisal procedure based on multiple leading factor the most according to claim 1, its feature exists In, step 8) described in distribution network reliability index, including system System average interruption frequency, system System average interruption duration, Average power supply availability and the total electricity of system are not enough.